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All Journal Buletin Peternakan Natural Science: Journal of Science and Technology Jurnal Ilmu Lingkungan Jurnal Natur Indonesia Microbiology Indonesia Jurnal Riset Kimia Jurnal Kimia dan Kemasan Jurnal Litbang Industri IJFAC (Indonesian Journal of Fundamental and Applied Chemistry) Jurnal Zarah Alotrop Jurnal Pendidikan dan Ilmu Kimia Sinkron : Jurnal dan Penelitian Teknik Informatika INTECOMS: Journal of Information Technology and Computer Science Jurnal Katalisator Jurnal Pascapanen dan Bioteknologi Kelautan dan Perikanan METIK JURNAL Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Analis Farmasi Jurnal Agrotropika Jurnal Kimia dan Kemasan JAF (Jurnal Analis Farmasi) Jurnal Litbang Industri Makara Journal of Science Data Sciences Indonesia (DSI) TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Journal of Engineering and Science Application
Abdi Dharma
Universitas Andalas
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Medicine & Pharmacology Physics Veterinary Other

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Tinjaun Literatur Sistematis Terhadap Teknologi Kecerdasan Buatan untuk Deteksi Nyeri (2020-2024) Dharma, Abdi; Veron, Veron; Wijaya, Jeremy; Valentino, Bue; Wijaya, Vincent
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1068

Abstract

Pain is a complex sensory and emotional experience, often difficult to assess objectively. In recent years, artificial intelligence (AI) has shown great potential in improving the accuracy and efficiency of pain assessment. This study aims to conduct a systematic review of AI-based pain detection methods developed in the period 2020 to 2024. Using the PRISMA 2020 approach, a literature search was conducted in three major databases: PubMed, Scopus, and Google Scholar, with keywords related to pain detection and perception. Of the 1,685 articles found, 44 studies were selected through a rigorous selection process. The analysis of five showed the main approaches in pain detection: Neuroimaging & Neurological, Physiological & Biometric, Visual-Only (facial recognition), Audio/Speech-based, and Behavioral/Observational. Neuroimaging-based approaches such as EEG and fMRI were the most dominant, followed by the use of biometric sensors and facial recognition technology. However, significant challenges remain, including the limitations of global data standards, difficulties in model generalization, and ethical and privacy issues. This study highlights that the integration of non-invasive sensors with deep learning models and personalized approaches can improve the effectiveness of automated pain detection systems.
Tren dan Potensi Sistem Informasi Geografis dalam Penanggulangan Demam Berdarah: Analisis Bibliometrik Crispin, Andrian Reinaldo; Edbert, Edbert; Hulu, Victor Trismanjaya; Kamble, Pratik Bibhisan; Dharma, Abdi
Data Sciences Indonesia (DSI) Vol. 5 No. 1 (2025): Article Research Volume 5 Issue 1, June 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dsi.v5i1.6351

Abstract

Demam berdarah dengue masih menjadi masalah kesehatan masyarakat yang signifikan di banyak negara. Tingginya prevalensi penyakit ini menunjukkan perlunya alat yang efektif seperti Sistem Informasi Geografis (SIG) untuk membantu memprediksi dan mengelola penyebarannya. Penelitian ini bertujuan untuk mengkaji dan merangkum peran SIG dalam pemetaan dan komunikasi pola transmisi dengue. Metode yang digunakan adalah pendekatan bibliometrik dengan pengumpulan literatur relevan dari beberapa basis data, seperti Google Scholar, Scopus, dan PubMed. Dari total 440 artikel yang diidentifikasi, hanya 11 yang memenuhi kriteria inklusi. Data yang dikumpulkan mencakup tahun publikasi (2013–2023), judul jurnal, desain studi, populasi, intervensi, hasil, serta manfaat yang dilaporkan dari penggunaan SIG dalam penelitian terkait dengue. Analisis kualitatif dilakukan dengan mengorganisasi dan mempresentasikan temuan utama dari studi yang terpilih. Hasil menunjukkan bahwa SIG sangat berguna dalam mengidentifikasi area wabah saat ini, mendeteksi zona berisiko tinggi melalui klaster spasial, meningkatkan akurasi prediksi kasus, serta mendukung upaya surveilans secara berkelanjutan. Selain itu, SIG juga berkontribusi pada pengambilan keputusan yang lebih tepat dalam program pencegahan dan pengendalian dengue. Secara keseluruhan, SIG memainkan peran penting dalam memahami dinamika penyakit, memperkuat sistem peringatan dini, dan membimbing respons kesehatan masyarakat terhadap wabah dengue.
Trends and Potential of Geographic Information Systems in Dengue Management: Bibliometric Analysis Crispin, Andrian Reinaldo; Edbert, Edbert; Hulu, Victor Trismanjaya; Kamble, Pratik Bibhisan; Dharma, Abdi
Journal of Engineering and Science Application Vol. 2 No. 2 (2025): October
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/jesa.v2i2.32

Abstract

Dengue fever remains a significant public health issue in many countries. Its high prevalence highlights the need for effective tools like Geographic Information Systems (GIS) to help predict and manage the spread of the disease. This study aims to examine and summarize the role of GIS in mapping and communicating dengue transmission patterns. A bibliometric approach was used to collect relevant literature from databases such as Google Scholar, Scopus, and PubMed. Out of 440 identified articles, only 11 met the inclusion criteria. Data extracted included publication years (2013–2023), journal titles, study designs, populations, interventions, outcomes, and reported benefits of GIS in dengue-related research. Qualitative analysis was conducted by organizing and presenting key findings. The results show that GIS is valuable in identifying current outbreak areas, detecting high-risk zones through spatial clustering, improving the accuracy of case predictions, and supporting ongoing surveillance efforts. Additionally, GIS contributes to more informed decision-making in dengue prevention and control programs. Overall, GIS plays an essential role in understanding disease dynamics, enhancing early warning systems, and guiding public health responses to dengue outbreaks.
Co-Authors - Afrizal Admin Alief Admin Alif Admin Alif Afriyanti Azhar Alif, Admin Anggela Marta Tasman Arif Juliari Kusnanda Armaini - Baharuddin Shaleh Bayu Afnovandra Perdana Candra, Windy Christnatalis Crispin, Andrian Reinaldo Dedi Nofiandi Delima Sitanggang, Delima Edbert, Edbert Edison Munaf Edison Munaf Elida Mardiah Eri Sulyanti Eti Farda Husin Eti Farda Husin HAFIL ABBAS Hafil Abbas Harvianti, Yuniar Hazli Nurdin Heyneker, Daniel Hulu, Victor Trismanjaya Husni Mukhtar I PUTU KOMPIANG I. P. Kompiang Indah Indah Indrawati - Indrawati Indrawati IRSAN RYANTO Jabang Nurdin Jamsari Jamsari Kamble, Pratik Bibhisan Lee Wah Lim MARBUN, ADVENT TORAS Mardi Turnip, Mardi MARIA ENDO MAHATA Marniati Salim Melona Siska Musifa, Eva Nasril Nasir Nasril Nasir Nasril Nasir Nasril Nasir Nasril Nasir Nurhamidah Oktaf Rina Oktoriza, Ghifarizka Periadnadi - Periadnadi Periadnadi PULUNGAN, JURMIDA PURBA, JOICE ANGELINA Rahmadani Wulandari Rahmatika Yani Rahmiana Zein Refilda Refilda Riska Hernandi Saragi, Yosua Morales Sekatresna, Widiyanti Shaleh, Baharuddin Siti Aisyah Siti Hajjir, Siti Sulyanti, Eri Sumaryati Syukur Suryani Suryani Syafriza Yanti Syafrizayanti, Syafrizayanti Syafrizayanti, Syafrizayanti Syafrizayanti, Syafrizayanti Syukri Arief Talib, Ramanisa Muliani Tania, Alinda Tarigan, Julio Putra Toyohide Takeuchi TRIMURTI HABAZAR Turnip, Josua Presen Valentino, Bue Vanness, Jeff Veron, Veron Wahida Nia Elfiza Warni, Mega Waruwu, Jefrin Widiyanti Sekatresna Wijaya, Eko Bambang Wijaya, Jeremy Wijaya, Vincent Wizna (Wizna) Wulandari, Rahmadani Yetria Rilda Yose Rizal Yoserizal Yoserizal Yunazar Manjang Yunazar Manjang Yunazar Manjang Zulkarnain Chaidir